> ## Documentation Index > Fetch the complete documentation index at: https://docs-docflow.textin.ai/llms.txt > Use this file to discover all available pages before exploring further. # Multi-Image Cropping > Intelligently recognize and crop documents containing multiple independent images on one page, supporting scenarios like expense receipt pasting ## Feature Overview The multi-image cropping function can automatically recognize multiple independent images or tickets contained in one page of a document and separately crop them into independent sub-documents. This is particularly useful for scenarios such as processing reimbursement attachments or scans containing multiple receipts. ## Use Cases ### 1. Expense Receipt Pasting Scenario An A4 paper with multiple tickets laid flat: * Train tickets * Flight itineraries * Multiple taxi invoices * Restaurant invoices Through the multi-image cropping function, each ticket can be separately recognized and cropped, facilitating subsequent classification and amount extraction. crop example ## API Parameter Configuration ### Enable Multi-Image Cropping Function Set `crop_flag=true` in the upload interface to enable the multi-image cropping function: ```bash curl icon=terminal wrap theme={null} curl -X POST \ -H "x-ti-app-id: " \ -H "x-ti-secret-code: " \ -F "file=@/path/to/multi-image-document.pdf" \ "https://docflow.textin.ai/api/app-api/sip/platform/v2/file/upload?workspace_id=&crop_flag=true" ``` ### Parameter Description | Parameter Name | Type | Default Value | Description | | -------------- | ------- | ------------- | ----------------------------------------------- | | `crop_flag` | boolean | false | Whether to enable multi-image cropping function | ## Example Code ```python Python expandable icon=python theme={null} import requests import json def upload_with_crop(file_path, workspace_id, app_id, secret_code): """ Upload file and enable multi-image cropping function """ url = "https://docflow.textin.ai/api/app-api/sip/platform/v2/file/upload" headers = { "x-ti-app-id": app_id, "x-ti-secret-code": secret_code } params = { "workspace_id": workspace_id, "crop_flag": "true" # Enable multi-image cropping function } with open(file_path, 'rb') as file: files = {'file': file} response = requests.post(url, headers=headers, params=params, files=files) return response.json() def fetch_crop_results(workspace_id, batch_number, app_id, secret_code): """ Query multi-image cropping results """ url = "https://docflow.textin.ai/api/app-api/sip/platform/v2/file/fetch" headers = { "x-ti-app-id": app_id, "x-ti-secret-code": secret_code } params = { "workspace_id": workspace_id, "batch_number": batch_number } response = requests.get(url, headers=headers, params=params) return response.json() def parse_crop_coordinates(from_parent_position_list): """ Parse cropping coordinate information Coordinate format: [x1, y1, x2, y2, x3, y3, x4, y4] Represents the four vertex coordinates of a rectangle """ if len(from_parent_position_list) != 8: return None coordinates = { "top_left": (from_parent_position_list[0], from_parent_position_list[1]), "top_right": (from_parent_position_list[2], from_parent_position_list[3]), "bottom_right": (from_parent_position_list[4], from_parent_position_list[5]), "bottom_left": (from_parent_position_list[6], from_parent_position_list[7]) } # Calculate bounding box x_coords = [coord[0] for coord in coordinates.values()] y_coords = [coord[1] for coord in coordinates.values()] bbox = { "x_min": min(x_coords), "y_min": min(y_coords), "x_max": max(x_coords), "y_max": max(y_coords), "width": max(x_coords) - min(x_coords), "height": max(y_coords) - min(y_coords) } return {"coordinates": coordinates, "bbox": bbox} # Usage example if __name__ == "__main__": # Configuration information WORKSPACE_ID = "your-workspace-id" APP_ID = "your-app-id" SECRET_CODE = "your-secret-code" FILE_PATH = "/path/to/multi-image-document.pdf" # Upload file and enable multi-image cropping upload_result = upload_with_crop(FILE_PATH, WORKSPACE_ID, APP_ID, SECRET_CODE) print("Upload result:", json.dumps(upload_result, indent=2, ensure_ascii=False)) # Get batch number batch_number = upload_result.get("result", {}).get("batch_number") if batch_number: # Query multi-image cropping results fetch_result = fetch_crop_results(WORKSPACE_ID, batch_number, APP_ID, SECRET_CODE) print("Multi-image cropping result:", json.dumps(fetch_result, indent=2, ensure_ascii=False)) # Parse coordinate information files = fetch_result.get("result", {}).get("files", []) for file in files: child_files = file.get("child_files", []) for child in child_files: if child.get("task_type") == 3: # Sub-file generated by multi-image cropping position_list = child.get("from_parent_position_list") if position_list: coord_info = parse_crop_coordinates(position_list) print(f"Coordinate information for sub-file {child.get('name')}:", coord_info) ``` ## Return Result Description ### Multi-Image Cropping Result Structure After enabling the multi-image cropping function, the result returned by the `file/fetch` interface will include the `child_files` field, which describes the information of sub-documents after cropping: ```json expandable theme={null} { "code": 200, "result": { "files": [ { "id": "parent-file-001", "name": "multi-image-document.pdf", "format": "pdf", "child_files": [ { "id": "child-001", "task_id": "task-001", "task_type": 3, // 3 indicates sub-file generated by multi-image cropping "name": "multi-image-document.pdf#1", "format": "pdf", "category": "invoice", "from_parent_position_list": [12, 30, 420, 30, 420, 320, 12, 320], "crop_info":{"page":0,"imageAngle":"0"} "status": "success" }, { "id": "child-002", "task_id": "task-002", "task_type": 3, "name": "multi-image-document.pdf#2", "format": "pdf", "category": "receipt", "from_parent_position_list": [450, 30, 800, 30, 800, 200, 450, 200], "crop_info":{"page":0,"imageAngle":"0"} "status": "success" } ] } ] } } ``` ### Key Field Description | Field Name | Type | Description | | ----------------------------------------- | ------- | ---------------------------------------------------------------------------------------------------------------- | | `child_files` | array | List of sub-files after cropping | | `child_files[].id` | string | Unique identifier of sub-file | | `child_files[].task_type` | integer | Task type, 3 indicates generated by multi-image cropping | | `child_files[].category` | string | Document classification result | | `child_files[].from_parent_position_list` | array | Coordinates of cropping area in original image, refer to [Coordinate System Description](../03-parse/coordinate) | | `child_files[].crop_info` | object | Detailed information of multi-image cropping, including page index and angle information |